42 results about "Language disorder" patented technology

The invention relates to the technical field of language barrier evaluation, and discloses a deep learning-based language barrier executive intervention effect evaluation method. The method comprises the following steps: acquiring real-time voice data and facial expression data of a language barrier patient in intervention training through a multi-modal data acquisition device to form an original behavior feature set; performing acoustic feature hierarchical analysis on the voice data by adopting a time sequence feature extraction network to generate a voice time sequence feature vector; performing micro-expression dynamic capture on the expression data through a three-dimensional convolutional neural network to generate an expression state feature vector; inputting the two types of vectors into a multi-modal feature fusion layer to carry out cross-modal correlation analysis, and generating a comprehensive behavior evaluation matrix; on the basis of the matrix, an intervention effect analysis model driven by an attention mechanism is adopted, a behavior improvement degree index of the current intervention stage is calculated, accurate evaluation of the intervention effect is achieved, and support is provided for dynamic adjustment of language barrier rehabilitation intervention.

To provide a system and method for providing speech instructions based on classification of speech of language communication from a user.SOLUTION: A computing system can generate speech characteristics of a first verbal communication using a first audio sample from a user. The computing system can determine a first speech classification of the first verbal communication based on the speech characteristics from a plurality of speech classifications. The computing system can select one action from a plurality of actions that includes modifying one or more speech characteristics that define a user's speech based on the first speech classification. The computing system can provide instructions to present a message prompting the user to perform the speech defined by this one action selected from the plurality of actions. The efficacy of the medication that the user is taking to address the condition can be increased.SELECTED DRAWING: Figure 1

A method for treating a language disorder in a patient includes receiving therapist input specifying a speech target and engagement indicator priority, capturing audio of a speech response to a therapy prompt, and identifying the language of the response using a multilingual language identification model. The method further comprises analyzing the speech response with a language-specific recognition model to extract speech features and classify errors across multiple linguistic and acoustic dimensions. Engagement indicators are extracted and used to compute an engagement score, which, along with the error classifications and speech target, informs a decision model that selects a therapy task. The selected task is presented to the patient, and a subsequent speech response is captured to update error classifications. The decision model is iteratively refined based on therapist input and revised error data, enabling adaptive, personalized therapy progression.

The invention discloses a wake-up method based on expression recognition, a robot and an interaction device capable of performing wake-up control through facial expressions of a user. The wake-up method and the robot are suitable for scenes such as psychological care, accompanying robots, child / old-age auxiliary equipment and the like. The device has multi-modal fusion perception and facial emotion active recognition awakening capability, and can remarkably improve the awakening accuracy, the humanization degree and the technical depth. By integrating an expression recognition awakening mechanism, the naturalness and initiative of man-machine interaction are improved, and the limitation of awakening depending on a single mode such as voice and touch control in the prior art is improved. The robot supports voice wake-up, touch wake-up and button wake-up modes at the same time, and a multi-mode fusion wake-up mechanism is achieved. The naturalness and usability of the psychological support robot in the man-machine interaction process are improved, and the psychological support robot is particularly suitable for non-contact emotion accompanying and psychological intervention of children, old people and language barrier users.

The invention relates to the technical field of computer software, and particularly discloses a brain voice evaluation method and system based on a DSM-V cognitive domain, and the method comprises the steps: obtaining the voice information of a user; feature extraction is carried out on the voice information based on a DSM-V cognitive domain to obtain spoken language feature information, and the spoken language feature information comprises vocabulary reaction feature information, vocabulary semantic feature information and vocabulary association feature information; according to the vocabulary reaction feature information, obtaining multiple stages of vocabulary feature information, and according to all the stages of vocabulary feature information, obtaining a vocabulary reaction feature evaluation value; and obtaining feature information of a plurality of vocabulary nodes according to the vocabulary semantic feature information. According to the method, a foundation is laid for comprehensive assessment by obtaining the voice information, multi-dimensional spoken language feature information is extracted based on the DSM-V cognitive domain, the brain voice function can be deeply analyzed, the problem that traditional assessment dimensions are single is solved, and for example, the root of the problem can be accurately positioned in language disorder diagnosis.

To provide a system that supports effective communication for those with language disorder by utilizing gestures and objects.SOLUTION: A system comprises a capturing unit, an analysis unit, a presentation unit, and a conversion unit. The capturing unit captures the user's gestures or objects. The analysis unit analyzes the video captured by the capturing unit. The presentation unit presents candidates based on the analyzed result. The conversion unit converts the candidates presented by the presentation unit into images, illustrations, or comics.SELECTED DRAWING: Figure 1

The application relates to the technical field of medical information, and specifically discloses a multi-modal Alzheimer's disease early screening algorithm based on a large language model. The algorithm first collects speech data and demographic information of participants. The speech data is processed through noise suppression, voice enhancement and speaker separation, and is transcribed into descriptive text. Then, the eGeMAPS feature set is extracted from the speech data and time-series spliced, and combined with the demographic information to form a multi-modal feature matrix. Key features are obtained using an attention pooling module, and feature classification is performed using a support vector machine to distinguish potential Alzheimer's disease patients from healthy individuals. The classification results, descriptive text and demographic information are input into the large language model, and zero-shot thinking chains are used to analyze four language barriers: reduced information content, lexical semantic defects, poor referential coherence and language loss of psychological state, and a comprehensive screening report is finally generated. The algorithm improves the accuracy of early diagnosis by combining audio and semantic features.

To provide a system capable of overcoming a linguistic barrier and allowing people around the globe to converse.SOLUTION: Provided is a system comprising: means for transcribing a conversation in association with a voice tool; means for interpreting the transcription into languages around the globe using a Chat GPT; and means for reproducing the interpreted transcription using the voice tool.SELECTED DRAWING: Figure 1

The present invention provides a method and apparatus for generating speech synthesis information, which relates to the technical field of speech data processing and can be used in the financial field or other technical fields. The method includes: obtaining a target video, and extracting human joint point features and lip language features according to the target video; the target video includes real-time images of customers with speech disorders; fusing the human joint point features and the lip language features to obtain a fused feature, and performing text recognition on the fused feature to obtain text vocabulary information; performing speech synthesis on the text vocabulary information to obtain speech synthesis information. The apparatus executes the above method. The method and apparatus for generating speech synthesis information provided by the embodiments of the present invention can accurately and efficiently identify the speech information that customers with speech disorders want to express, and improve the business handling efficiency.

The invention belongs to the field of intelligent medical rehabilitation engineering, particularly relates to a speech recognition-based speech disorder adjuvant therapy system, and solves the problems of high pathological speech misjudgment rate, large dialect interference and single feedback in the prior art. A phoneme fault-tolerant threshold value is dynamically adjusted by constructing an adaptive speech recognition engine, regional features and pathological features are separated by using a dialect adaptation module, and three-dimensional simulation, AR real-time correction and touch graded vibration of vocal organs are realized in combination with a multi-modal feedback device; the pathological speech recognition precision is improved; and the neural remodeling efficiency is optimized.

The invention discloses a big language model security test method and system based on a small language cross-language attack. The method comprises the steps of constructing a small language selection strategy library, designing a cross-language semantic conversion engine, constructing a multi-dimensional language barrier, implementing a self-adaptive language switching mechanism and establishing a cross-language security evaluation system. According to the method, through dual language barriers of minority language input and Chinese output, a traditional single-language security detection system is effectively bypassed, attack content is presented in a minority language form, but a target model is forced to reply with Chinese, and a language understanding gap is established between input and output; the dynamic language switching strategy realizes intelligent cross-language attack, and the attack method can be adjusted in real time according to the defense response of the target model. According to the method, the adaptability, the concealment and the overall test effect of attacks are remarkably improved, and a systematized and efficient technical means is provided for large model security assessment in a multi-language environment.

The application relates to a development language disorder early identification method and system fusing neural activity features and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring original neurophysiological signals and matched clinical information, and constructing a data set; power features and coherence features of the signals are normalized to generate enhanced feature vectors; attention weighted feature vectors are obtained through mutual information based attention mechanism weighting; the radial basis function is used to nonlinearly map the feature vectors to a high-dimensional space to obtain extended feature vectors; a development language disorder early identification model is constructed, brain region level feature aggregation and modulation, clinical factor fusion and gate modulation are adopted, a decision function fusing nonlinear interaction items is introduced, and a binary cross entropy loss function is used to optimize the model; after model training is completed by using a training set, signals of a subject to be evaluated are input into the model after the same preprocessing, and an identification result is output. The application can improve the accuracy of development language disorder early identification.

According to an embodiment, a device for script extraction and subtitle transmission synchronized with live performing art content is provided. When a viewer views verbal performing arts such as plays or musicals, the device projects commentary subtitles synchronized in real time with performance content in a preferred language in front of eyes by using a display device including AR smart subtitle glasses, in order to eliminate a language barrier due to nationality or an auditory barrier caused by hearing impairment or hearing loss and enable viewing of the performing arts, so that the subtitles can be viewed in synchronization with the performance.

The invention discloses an adaptive bilingual scientific education content intelligent recommendation system, which belongs to the technical field of intelligent education recommendation systems, is particularly suitable for primary school multi-language background students, and comprises a learner model construction engine, a multi-language resource matching module, a learning path optimization module, a content difficulty adjustment module and a teacher support module. The scientific concept understanding degree and the language proficiency degree of students are subjected to two-dimensional modeling, the bilingual content proportion is dynamically adjusted based on a language ability self-adaptive weighting strategy, scientific knowledge acquisition and language ability development goals are collaboratively optimized, a personalized bilingual learning path is generated, and actual deployment shows that the system enables the scientific score to be improved by 32%, the English vocabulary amount to be increased by 45% and the learning efficiency to be improved by 30%. The influence of language barriers on scientific learning is effectively solved, and the dual purposes of scientific education and language education are achieved.

1. Name of the product in this design: Speech Communication Assistive Training Device. 2. Purpose of this design: To provide speech training or assist communication for people with language impairments. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

To remove the language barrier between a person with hearing disabilities and a listener, and allow the person with hearing disabilities wearing gloves to communicate in sign language which is to be converted into voice or characters in real time, thereby realizing smooth interaction.SOLUTION: A glove sign language voice system includes: sign language recognition means for reading, by a sensor, hand gestures and facial expressions of a person with hearing disabilities who is wearing gloves, and converting them into voice or characters in real time; sign language analysis means for performing accurate sign language recognition and expression analysis utilizing sign language data and AI technology; and voice output means for realizing smooth interaction between the person with hearing disabilities and the listener.SELECTED DRAWING: Figure 1

The invention relates to a neural activity feature fused developmental language disorder early recognition method and system, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring an original neurophysiological signal and matched clinical information, and constructing a data set; performing normalization processing on the power feature and the coherence feature of the signal to generate an enhanced feature vector; obtaining an attention weighted feature vector through attention mechanism weighting based on mutual information; performing nonlinear mapping to a high-dimensional space by using a radial basis function to obtain an extended feature vector; the method comprises the following steps: constructing a developmental language disorder early recognition model, introducing a decision function fused with a nonlinear interaction item by adopting brain region level feature aggregation and modulation, clinical factor fusion and gating modulation, and optimizing the model by a binary cross entropy loss function; and after model training is completed by using the training set, inputting a to-be-evaluated tested signal into the model after same preprocessing, and outputting an identification result. According to the invention, the accuracy of early recognition of the developmental language barrier can be improved.

A method, server, and computer-readable medium for detecting cognitive and language disorders. A computer-implemented method for assessing the presence of a condition in a subject is provided, the method comprising: generating facial landmarks on a received input video to define points associated with regions of interest on the subject's face; defining speech periods based on respective positions of the defined landmarks; measuring pause frequency, repetition patterns, and lexical variation during the speech periods without determining or applying semantic information associated with the speech to generate an overall score; and generating a prediction of the presence of the condition in the subject, associated with the overall score, based on the overall score.

The invention discloses a language disorder assessment method and system, and belongs to the technical field of data processing, and the method comprises the steps that a user side accesses a language assessment platform, a language cognition task is generated, the language cognition task comprises a main language task and a secondary cognition task, and task sequence generation is carried out with cognition load increase; issuing the language cognition task to a user side thread, executing a task language test, and returning a task language flow; and a cognitive evaluation module embedded in the language evaluation platform is triggered, cascade evaluation based on logic paradox, language entropy change and a high-dimensional semantic network is executed, a language evaluation result is generated, and popup window display is performed on a platform user side. According to the method and the device, the technical problem that potential or slight language barriers are difficult to effectively induce and detect due to single language evaluation environment and lack of cognitive pressure in the prior art is solved.

Pharmacological methods and single unit dosage forms for treating the expressive language deficit in an autistic human child or adult are provided. A therapeutically effective dose of enantiomerically enriched R-ethosuximide or a pharmaceutically acceptable salt thereof is administered to a patient suffering from expressive language deficit, preferably over an extended period, e.g., six months or longer, to reduce the autistic patient's expressive language deficit.

The invention discloses a psychological health coach voice model optimization method based on large language model driving, and the method employs a voice signal preprocessing module, a multi-modal emotion feature extraction module, a dynamic weight distribution module, a large language model reasoning module, a voice synthesis optimization module, and a hardware cooperation acceleration module which are sequentially connected in series through a data bus. The dynamic weight distribution module is in two-way communication with the multi-modal emotion feature extraction module and the large language model reasoning module, and the hardware collaborative acceleration module is in parallel connection with the large language model reasoning module through a PCIe channel; according to the invention, through the multi-modal feature fusion (voice, text and micro-expression) and dynamic weight distribution technology, the emotion recognition precision is obviously improved, and the complex emotion state of a user is effectively captured; the dialect self-adaption unit breaks through regional language barriers through accent conversion mapping, and the dialect user interaction effectiveness is improved.

1. The name of the design product: language development disorder brain magnetic diagnostic instrument. 2. The use of the design product: application instrument for diagnosing autism and other language disorder children. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view. 5. The bottom of the design product is not easy to see or not visible during use, omit the top view.

To overcome the barrier of languages, automatically translate speech of the other person into the native language of the user, and provide an answer.SOLUTION: A system for overcoming the barrier of languages includes means for automatically translating speech of the other person into the native language of a user; and supporting an answer on the basis of the translated speech.SELECTED DRAWING: Figure 1

To provide a system according to an embodiment which can properly convey intents or emotions of people with language disorders.SOLUTION: The system according to an embodiment includes a collection unit, an analysis unit, an estimation unit, and a provision unit. The collection unit collects eye-level data and tone data in the daily life of a user. The analysis unit analyzes the eye-level data and the tone data collected by the collection unit. The estimation unit estimates an intent or an emotion of a user on the basis of the data analyzed by the analysis unit. The provision unit outputs information which fits the needs of the user on the basis of the intent or the emotion estimated by the estimation unit.SELECTED DRAWING: Figure 1

To provide a system which eliminates the wall of languages, and allows inter-cultural communication to be conducted smoothly.SOLUTION: A language understanding spectacle system includes: means for translating a language in real time by using a natural language processing technique; and means for visually displaying a translation result via smart glasses.SELECTED DRAWING: Figure 1

The present invention relates to a method for treating non-neurodegenerative diseases, comprising administering to a subject in need thereof an effective amount of turmeric oil, wherein the oil is obtained from rhizomes of Curcuma longa L., and wherein the non-neurodegenerative diseases include upper motor neuron syndrome, lower motor neuron syndrome, spastic hemiparesis, tetraparesis, diparesis, monoparesis, flaccid hemiparesis, cerebral palsy, spasticity, autism, dysarthria, communication, speech, and language disorders.

According to one embodiment, a method, computer system, and computer program product for language development is provided. The embodiment may include identifying one or more speech goals of a user within input of the user to a conversational chatbot. The embodiment may include forwarding the identified speech goals and the input of the user to a large language model (LLM) utilized by the conversational chatbot. Based on the identified one or more speech goals and the input of the user, the embodiment may include retrieving expert-crafted prompts for use with the LLM. The embodiment may include generating, via the LLM in combination with the retrieved expert-crafted prompts, a response to the user. The response addresses an identified speech goal of the user. The embodiment may include sending, via the conversational chatbot, the response to the user.

The invention belongs to the technical field of equipment control, and particularly relates to a wearable equipment control method and system based on AI vision and behavior prediction, and the method comprises the steps: obtaining intelligent wearable equipment data, and carrying out the preprocessing; allocating a pseudo name identifier to the multi-modal feature set, and constructing a time sequence causal chain of the perception data and the behavior intention; generating a lightweight model according to the intention probability distribution, and pre-generating a voice feedback text by event driving; a mapping model is trained according to the voice feedback instruction set and the head micro-deformation signal, and a control instruction is generated through matching; updating visual, auditory and language AI models through federal learning; and according to the optimized AI model and the labeled field data, generating a pseudo tag adaptation model through neighbor semi-supervision, and outputting a wearable device control scheme. The AI + AR technology integrates the four functions of vision, hearing, language and brain power, and the problems of life self-care and social communication pain points of people suffering from vision, hearing and language disorders and mild cerebral palsy are solved.

A pharmacological method for treating the expressive language deficit in an autistic human child or adult is provided. A therapeutically effective dose of a succinimide anticonvulsant, e.g., ethosuximide, methsuximide, phensuximide, or a pharmaceutically acceptable salt thereof, is administered to a patient suffering from expressive language deficit, preferably over an extended period, e.g., six months or longer. Language gains are retained even after treatment is discontinued.